Is Impaired Sleep Quality a Triggering Factor in Melasma Patients? A Cross-Sectional Study

Abstract

Background:

Sleep disorders trigger the hormonal imbalance and the accumulation of reactive oxygen molecules which are involved in melasma pathogenesis.

Aims and Objectives:

This study aims to assess the potential relationship between melasma and sleep components.

Material and Methods:

One hundred patients with melasma and 100 sex- and age-matched healthy controls aged over 18 were included. The melasma area severity index (MASI) and melasma quality of life (MelasQoL) scores of the patients were calculated. The Pittsburg Sleep Quality Index (PSQI) and the Epworth Sleepiness Scale (ESS) were applied to patients with melasma and healthy controls.

Results:

Compared with the controls, the median PSQI and ESS total scores were higher in the melasma patients. The patients with melasma reported impaired sleep components more frequently than the healthy controls. The rate of cases with excessive daytime sleepiness was similar between the patients and the controls. The analysis did not reveal any statistically significant correlation between MASI, MelasQoL, and the two questionnaires for melasma patients. In the multivariate analyses, the following factors were found to affect melasma: subjective sleep quality score (OR: 2.49, 95%CI: 1.26–4.89); sleep latency score (OR: 2.16, 95%CI: 1.34–3.49), sleep disturbances score (OR: 2.78, 95%CI: 1.17–6.57), Fitzpatrick skin type (OR: 1.88, 95% CI: 1.15–3.07), and total ESS score (OR: 1.13, 95% CI: 1.04–1.23).

Conclusion:

Our study’s findings suggest impaired subjective sleep quality, prolonged sleep onset latency, and sleep disturbances may affect melasma. Dermatologists should consider the potential benefits of improving sleep hygiene and treating sleep disorders in melasma patients.

Introduction

Melasma is a chronic acquired hyperpigmentation disorder characterized by irregularly circumscribed, brown macules and plaques on sun-exposed areas, principally on the face. This skin disorder is frequently observed in dark-skinned women.[1] Its prevalence varies between 1% to 50% depending on the ethnicity, skin type, and intensity of ultraviolet (UV) exposure.[2] Although the underlying mechanism of melasma is not fully understood, many factors are blamed for its etiology. The most important factors are UV exposure, genetic predisposition, and hormonal effects (pregnancy, hormone replacement therapies, oral contraceptives, and corticosteroid use).[1,3]

Studies indicate that oxidative stress is associated with melasma pathogenesis.[4] Some showed an imbalance between the serum oxidant and antioxidant markers in melasma patients.[4,5,6] Kim and Lee[7] demonstrated that oxidative stress in melasma inhibits the ciliogenesis and hedgehog signaling pathway in lesional keratinocytes due to the downregulation of nuclear factor E2-related factor 2, a regulator of cellular antioxidant defences. This leads to keratinocyte differentiation, melanin synthesis, and melanosome transfer, causing skin hyperpigmentation. Prolonged sleep deprivation reduces the anti-oxidative mechanisms, leading to the accumulation of reactive oxygen molecules.[8] In addition, sleep deprivation disrupts the regulation of female sex hormones, such as gonadotropins, progesterone, luteinizing hormone, and estradiol, which play a role in melanogenesis.[9,10]

Although the available data suggest a potential link between sleep health and melasma, this issue has yet to be researched. If this hypothesis is true, advising sleep hygiene practices and treating sleep disorders may benefit patients with melasma. The study aimed to examine the potential link between melasma and different aspects of sleep health using the Pittsburgh Sleep Quality Index (PSQI) and the Epworth Sleepiness Scale (ESS) in melasma patients.

Materials and Methods

This cross-sectional study took place at the Dermatology Outpatient Department of a university hospital from December 2022 to October 2023. One hundred patients with melasma and 100 sex- and age-matched healthy volunteers aged over 18 were included in the study. Cases with other pigmentation disorders, taking medicine for systemic disease, and patients with skin disorders including psoriasis, atopic dermatitis, urticaria, alopecia and skin sensitivity leading to poor sleep quality were excluded from the study. Pregnant cases and melasma patients under melasma treatment for six months were also excluded.

Sociodemographic data, drug usage (oral contraceptives, photosensitizing drugs, hormone replacement therapies, systemic corticosteroids), and family history of melasma were documented. Patients’ skin types were assessed according to the Fitzpatrick classification (I–VI).

Clinical data were assessed after the approval of the Dokuz Eylül University Faculty Non-Interventional Research Ethics Committee (Date: 21.12.2021; Number: 2022/41-08). Informed consent was obtained from the involved patients and healthy controls in the study.

The severity of melasma in patients was measured using the Melasma Area Severity Index (MASI).[11] The Melasma Quality of Life Scale (MelasQol), validated by Dogramacı et al.,[12] was used to assess the quality of life of the melasma patients.

The Pittsburgh Sleep Quality Index (PSQI) is a questionnaire that assesses various aspects of sleep quality, such as how long it takes to fall asleep, how well you sleep, and whether you use sleep medication. Each aspect is scored from 0 to 3, with 3 indicating poorer sleep quality. The range of potential scores is 0-21, with scores greater than five indicating impaired sleep quality.[13,14]

To determine daytime sleepiness, the Epworth Sleepiness Scale (ESS), validated by Izci et al., was used. The questionnaire includes eight carefully designed items to assess the likelihood of excessive daytime sleepiness. Each item is rated from 0 to 3 based on the probability of dozing off during an activity. A total score of 10 or higher indicates excessive daytime sleepiness, potentially indicating underlying health issues.[15,16]

Statistical methods

The normality of variables was assessed using the Kolmogorov-Smirnov and Shapiro-Wilk tests. The Mann–Whitney U test was used because all the quantitative independent data were distributed asymmetrically. The qualitative data were compared between the groups using Pearson’s Chi-square test or Fisher’s exact test. Logistic regression analysis was used to explore the factors that affect melasma. SPSS 28.0 program was used in the analyses. All tests were two-tailed, and P values less than 0.05 were considered statistically significant.

Because no previous studies were available on this topic to guide a simple size calculation, we performed a post-hoc power analysis using the observed differences between the melasma and control groups. The calculated statistical power for both the ESS total score and the global PSQI score comparisons was 99% (α = 0.05, two-tailed).

Results

Patient characteristics and risk factors of melasma

The study involved 100 patients with melasma, of whom 93% were female. The control group included 100 sex- and age-matched healthy volunteers. The mean age of the patients was 44.7 ± 9.3 years. The body mass index, education level distribution, residential location, and occupation were similar between patients with melasma and healthy controls. The detailed sociodemographic data of the patients with melasma and healthy controls are presented in Table 1.

Table 1.

Characteristics of melasma patients and the healthy control group

Variables		Melasma Group				Control Group			Median	P
		Mean±SD/n%			Median	Mean±SD/n%
Age		43.1	±	0.185	43.0	45.7	±	11.1	45	0.185	m
Gender	Male	7	1.000	7.0%		7		7%		1.000	X²
	Female	93		93.0%		93		93%
BMI		24.8	±	0.225	24.2	25.4	±	3.7	24.6	0.225	m
Education	Primary school	12	0.595	12.0%		13		13%		0.595	X²
	Middle school	4		4.0%		6		6%
	High school	30		30.0%		22		22%
	University	54		54.0%		59		59%
Occupation	Housewife	25	0.402	25.0%		32		32%		0.402	X²
	Public Servant	47		47.0%		34		34%
	Laborer	4		4.0%		3		3%
	Retiree	10		10.0%		12		12%
	Freelance	14		14.0%		19		19%
Working Actively?	No	34	0.658	34.0%		37		37%		0.658	X²
	Yes	66		66.0%		63		63%
Residential location	Urban (city)	91		91%		94		94%		0.421	X²
	Rural	9		9%		6		6%

^mMann–Whitney U test/X^² Chi Squared test. BMI, body mass index; SD, standard deviation

The mean MASI score of the patients was 7.5 ± 5.5 (range: 0.8-29.4) and the mean MelasQoL score was 19.9 ± 9.7 (range: 10-58). There was a statistically significant positive correlation between the MASI and MelasQoL in patients with melasma (r: 0.25, p: 0.013).

When comparing the risk factors between the study groups, we found that the melasma group had a significantly higher frequency of smoking, alcohol consumption, history of corticosteroid use, and number of pregnancies compared to the healthy controls. The incidence of darker skin types and family history of melasma was also higher in melasma patients than in the healthy controls [Table 2].

Table 2.

Comparison of risk factors of melasma between the study groups

Variables		Melasma Group				Control Group				P
		Mean±SD/n%			Median	Mean±SD/n%			Median
Smoking	Non-smoker	45		45%		66		66%		0.011X²
	Ex-smoker	17		17%		12		12%
	Smoker	38		38%		22		22%
Smoking (pack/year)		14.3	±	12	13	11.9	±	19.1	5	0.1	m
Alcohol consumption	(−)	50		50%		65		65%		0.032	X²
	(+)	50		50%		35		35%
Coffee intake	(−)	12		12%		21		21%		0.086	X²
	(+)	88		88%		79		79%
Coffee intake (cups/day)		2.1	±	1.4	2	1.9	±	1.2	1	0.262	m
Previous Pregnancy	(−)	17		18.3%		24		25.8%		0.216	X²
	(+)	76		81.7%		69		74.2%
Pregnancy Count		2.4	±	0.9	2.0	2.1	±	1.0	2.0	0.034	m
History of OCP use	(−)	53		57.0%		53		57.0%		1.000	X²
	(+)	40		43.0%		40		43.0%
Hormone Replacement Therapy	(−)	83		88.3%		83		88.3%		1.000	X²
	(+)	11		11.7%		11		11.7%
Systemic corticosteroid	(−)	82		82.0%		94		94.0%		0.009	X²
	(+)	18		18.0%		6		6.0%
History of infertility	(−)	92		92.0%		97		97.0%		0.121	X²
	(+)	8		8.0%		3		3.0%
History of photosensitive medication use	(−)	89		89.0%		95		95.0%		0.118	X²
	(+)	11		11.0%		5		5.0%
Fitzpatrick skin type	II	8		8.0%		17		17.0%		0.016	X²
	III	30		30.0%		36		36.0%
	IV	51		51.0%		45		45.0%
	V	11		11.0%		2		2.0%
Family history of melasma ( first degree)*	(−)	59		59%		57		57%		0.037	X²
	(+)	23		23%		43		43%

^mMann–Whitney U test/X^² Chi Squared test–missing data: 18 in the healthy control group. OCP, oral contraceptive pill; SD, standard deviation

Differences in the sleep components and excessive daytime sleepiness between patients with and healthy controls

The scores of the four components of the PSQI were significantly higher in the melasma patients compared to the controls. Patients with melasma reported poor sleep quality more frequently (n: 60, 60%) than the healthy controls (n: 34, 34%) [Table 3]. No statistically significant correlation was observed between MASI, MelasQoL, and total PSQI scale in melasma patients (Spearman’s analysis r: 0.023, p: 0.82; r: 0.04, p: 0.7; respectively).

Table 3.

Differences in the sleep components and sleepiness scale between the study groups

	Control Group				Melasma Group				P
	Mean±SD/n%			Median	Mean.±SD/n%			Median
Epworth Sleepiness Scale Total Score	4.8	±	3.9	4.0	7.3	±	4.3	7.0	<0.001	m
Pathological sleepiness
(ESS ≤10)	88		88.0%		80		80.0%		0.123	X²
(ESS >10)	12		12.0%		20		20.0%
Pittsburgh Sleep Quality Index
Subjective sleep quality	0.78	±	0.56	1.00	1.34	±	0.71	1.00	<0.001	m
Sleep latency	0.76	±	0.67	1.00	1.50	±	1.03	1.00	<0.001	m
Sleep duration	0.83	±	0.89	1.00	0.97	±	0.99	1.00	0.377	m
Habitual sleep efficiency	0.07	±	0.41	0.00	0.03	±	0.30	0.00	0.319	m
Sleep disturbances	0.96	±	0.45	1.00	1.40	±	0.55	1.00	<0.001	m
Use of sleeping medication	0.01	±	0.10	0.00	0.19	±	0.69	0.00	0.016	m
Daytime dysfunction	0.36	±	0.63	0.00	0.50	±	0.82	0.00	0.485	m
Global PSQI score	3.77	±	2.05	3.00	5.93	±	2.85	5.00	<0.001	m
Sleep quality
Bad	66		66.0%		40		40.0%		<0.001	X²
Good	34		34.0%		60		60.0%

^mMann–Whitney U test/X^² Chi Squared test. Bad, (Global PSQI score, >5); Good, (global PSQI score, ≤5); ESS, Epworth Sleepiness Scale; PSQI, Pittsburgh Sleep Quality Index

The rate of cases with excessive daytime sleepiness according to the cut-off value of >10 points was higher in the melasma patients (n: 20, 20%) than in the controls (N: 12; 12%). However, the difference was not statistically significant [Table 3]. The study findings showed no connection between MASI, MelasQoL, and ESS total score in melasma patients (Spearman’s analysis r: 0.045, p: 0.65; r: 0.042, p: 0.68, respectively). The frequency of excessive daytime sleepiness was statistically higher in melasma patients with overweight or obesity (n: 13/45; 28.9%) than in melasma patients with a healthy weight (28.9% vs 12.7%; p: 0.044).

Univariate and multivariate analysis of the factors affecting melasma

In the univariate analyses of the melasma risk factors in Table 2, smoking, history of corticosteroid use, Fitzpatrick skin type, total ESS scores, and the scores of the three sub-components of the PSQI (subjective sleep quality, sleep latency, and sleep disturbances) were the significant factors affecting melasma. The odds ratios and their corresponding 95% confidence intervals are displayed in Table 4.

Table 4.

Logistic regression analysis of the factors affecting melasma

	Univariate Analysis					Multivariate Analysis
	OR	%95 CI			P	OR	%95 CI			P
Smoking	2.17	1.23	-	3.83	0.007	-	-	-	-	-
History of steroid use	3.43	1.3	-	9	0.013	-	-	-	-	-
Fitzpatrick skin type	1.72	1.19	-	2.49	0.004	1.88	1.15	-	3.07	0.01
Epworth Sleepiness Scale	1.16	1.01	-	1.24	<0.001	1.13	1.04	-	1.23	0.006
Pittsburgh Sleep Quality Index	1.44	1.25	-	1.65	<0.001
Subjective sleep quality	4.17	2.41	-	7.22	<0.001	2.49	1.26	-	4.89	0.008
Sleep latency	2.63	1.82	-	3.81	<0.001	2.16	1.34	-	3.49	0.001
Sleep disturbances	6.33	3.11	-	12.89	<0.001	2.78	1.17	-	6.57	0.02

Logistic regression analysis (Forward LR). OR, Odds ratio; CI, confidence interval

In the multivariate analyses, subjective sleep quality score (OR: 2.49, 95%CI: 1.26–4.89); sleep latency score (OR: 2.16, 95%CI: 1.34–3.49), sleep disturbances score (OR: 2.78, 95%CI: 1.17–6.57), Fitzpatrick skin type (OR: 1.88, 95% CI: 1.15–3.07), and total ESS score (OR: 1.13, 95% CI: 1.04–1.23) were the significant independent factors that affecting melasma [Table 4].

In the control group family history of melasma was reported in 23% (OR: 1.93, 95% CI: 1.03–3.6, P = 0.038). Eighteen percent of the healthy control group did not respond to the question, so this variable was excluded from the multivariate analysis.

Discussion

Melasma is a chronic multifactorial disease whose etiopathogenesis is not fully understood.[1,3] An imbalance between serum oxidant and antioxidant markers has been observed in patients with melasma, which disrupts the formation of primary cilia in keratinocytes. Primary cilia play an inhibitory role in melanogenesis; therefore, their inhibition can potentially lead to increased melanin synthesis, melanosome transfer, and skin hyperpigmentation.[7] Poor sleep quality may disrupt antioxidant systems, leading to increased accumulation of oxygen radicals and subsequent skin inflammation. Furthermore, sleep deprivation can disturb the hormonal balance of progesterone, estradiol, luteinizing hormone, and prolactin. Research has shown that the levels of these hormones, which are involved in melanogenesis, vary between individuals with melasma and healthy controls.[8,9,10] However, to our knowledge, it has not been evaluated whether patients with melasma have impaired sleep quality. Our study demonstrated that more than half of patients with melasma (66%) reported poor sleep quality. Recent studies have shown the association of poor sleep quality with various chronic inflammatory skin disorders, including psoriasis, chronic spontaneous urticaria, and atopic dermatitis.[17,18] In a retrospective study, patients with rosacea reported poor sleep quality more frequently than the healthy controls. In addition, there was a positive correlation between the rosacea severity score and the PSQI score.[19] In our study, although melasma patients had higher PSQI scores than the healthy controls, no correlation was found between the PSQI and MASI scores. This result suggests that there may be a nonlinear relationship between poor sleep quality and the severity of melasma. Impaired sleep quality may maintain the chronic hypermelanocytic conditions rather than affecting the disease severity.

In the multivariate analysis of the components of the PSQI, it was found that for each unit increase in the scores of subjective sleep quality, sleep latency, and sleep disturbances, the odds of melasma were approximately doubled. Supporting our results, a study evaluating two groups of healthy women aged 30–50 with good and poor sleep quality determined that chronically poor sleep quality was associated with irregular pigmentation, fine wrinkles, loose skin, and loss of subcutaneous fat tissue, signs of accelerated ageing.[20] In addition, in a preliminary study, topical and systemic forms of melatonin treatment, an endogenous hormone negatively affected by sleep deprivation, were reported to be effective in melasma patients.[21] Further research is necessary to verify the impact of melatonin treatment on melasma patients with sleep disturbances. Advising patients with melasma on fundamental sleep hygiene practices may enhance melasma treatment outcomes. Avoiding napping, caffeine and alcohol intake, regular exercise, keeping regular sleep timing, having a quiet and dark sleep area, and having an appropriate temperature can improve sleep in patients with poor sleep quality.[22]

In our study, we found that the total ESS scores were notably greater in melasma patients than in healthy controls. Although the incidence of Epworth sleep disorder, according to the cut-off point of 10, is higher in melasma patients, the difference did not achieve significance. ESS evaluates the self-reported daytime sleepiness in various everyday situations, the primary cause of which is obstructive sleep apnea (OSA).[23] A retrospective study found that patients with rosacea had a 3.4-times higher relative risk of OSA than those without rosacea.[24] Psoriasis, atopic dermatitis, and hidradenitis suppurativa are the other inflammatory dermatologic conditions that are linked to OSA. Obesity and allergic rhinitis were the important predisposition factors in these disorders.[25] Consistent with the literature, the frequency of excessive daytime sleepiness was statistically higher among melasma patients who were overweight or obese compared to those with a healthy weight in our study. The ESS score was also determined as an independent influencing factor in our study. Therefore, melasma patients with high body mass index and concomitant OSA may benefit from weight loss and positive lifestyle changes.

Sampaio Xerfan et al.[26] suggested that melasma itself may affect sleep quality directly or by causing stress, which may negatively affect melasma pathology. However, we did not find any correlation between the MASI, MelasQoL, and the total scores of the questionnaires. There are conflicting results in the literature regarding the effect of melasma severity on the patients’ quality of life. Various studies demonstrated the correlation between MASI and MelasQoL, while some did not.[8,9,10] Our study showed a limited but significant correlation between the MASI and MelasQoL in melasma patients. However, the patient’s sleep quality was not linearly affected, suggesting the impairment is irrespective of the melasma condition.

There are some limitations in our study. We could not administer a questionnaire related to sun exposure to patients. However, we found no significant difference between our patients’ and controls’ educational status, occupation, and residential location, all closely related to sun exposure. This confidence leads us to believe these limitations should not significantly impact our results. In addition, the diagnoses of sleep disorders determined by the questionnaire instruments could not be confirmed by polysomnography.

In conclusion, individuals with melasma showed notably higher average PSQI and ESS scores compared to those in the control group. Excessive daytime sleepiness was more prevalent in melasma patients who were overweight or obese compared to those with a healthy weight. The total ESS score and impaired subjective sleep quality, the duration of falling asleep, and sleep disturbances of PSQI were the significant factors affecting melasma. Our findings suggest that various sleep disorders may contribute to the development of melasma. Gaining a deeper understanding of the causes and progression of this complex disease could significantly improve its management. Dermatologists should take into account the potential benefits of improving sleep hygiene and treating sleep disorders in melasma patients. More research is necessary to understand how enhancing sleep quality affects melasma treatment.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Nil.